902 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" uni jobs at Nature Careers
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: Joining an energetic, intellectually vibrant, and collegial lab team. Opportunities to learn, grow as an administrative professional, and be mentored. Joining the vibrant University of Washington research
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quality of care in hospitalized or critically ill patients. Using physiologic monitoring devices and digitized patient data, we implement statistical and machine learning decision support tools to detect
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this but have hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, things are rapidly changing. This project is part of a
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Usability evaluation Geographical and spatiotemporal data on environmental and socioeconomic context Ideal expertise/experience includes: Advanced machine learning (deep learning, representation learning
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outstanding researchers with a strong track record of advancing the state of the art in machine learning and potentially its application to biology and biomedicine, with the ambition to build an internationally
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(e.g. Nextflow) and cloud compute environments (e.g. OCI, AWS, GCP) Familiarity with Bayesian methods, machine learning, or causal inference in the context of biological data Contributions to open-source
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About the School SDEM integrates technology, economics, and management to cultivate versatile, innovation-driven leaders with global perspective. Hiring Clusters · Data Science & AI: machine learning
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. Collaborate with interdisciplinary EIT Oxford teams to link fundamental cell-developmental genetics research to machine-learning models designed to augment the search for relevant target genes. Requirements
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related field. Demonstrated Expertise in one or more of the following areas: Bio and AI: Theoretical and computational biophysics Machine learning and data analysis for biological systems Biomedical imaging
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artificial intelligence, machine learning, and the life sciences to shape the future of data-driven biology and biomedicine. We are seeking visionary researchers whose work pushes the boundaries of AI-enabled